基于混合多智能体遗传算法的作业车间调度问题研究

发布时间：2018-01-21 12:28

  本文关键词： 作业车间调度(JSP) 多智能体 遗传算法 邻居交互算子 自适应模拟退火算法(ASA)　出处：《北京航空航天大学学报》2017年02期 　论文类型：期刊论文

【摘要】：针对作业车间调度问题(JSP)的非确定性多项式特性与解空间分布的大山谷属性,本文提出一种多智能体遗传算法(MAGA)与自适应模拟退火算法(ASA)的混合优化算法,用于寻找最大完工时间最短的调度。首先,将每个染色体视作独立的智能体并采用工序编码方式随机初始化每个智能体,结合多智能体协作与竞争理论设计了实现智能体之间交互作用的邻居交互算子,进而利用一定数量智能体进行全局搜索,找到多个适应度较高的可行解。其次,为避免算法陷入局部最优,采用ASA对每个智能体开展局部寻优。最后,通过基准测试库中典型实例的计算结果验证了该算法的有效性。
[Abstract]:For the Job-shop scheduling problem (JSP), the non-deterministic polynomial property and the large valley attribute of the solution space distribution are discussed. In this paper, a hybrid optimization algorithm named Multi-Agent genetic algorithm (MAGA) and Adaptive simulated annealing algorithm (ASA) is proposed, which is used to find the schedule with the shortest completion time. Each chromosome is regarded as an independent agent and each agent is initialized randomly by the process coding method. A neighbor interaction operator is designed to realize the interaction between agents combined with the theory of multi-agent cooperation and competition. Then a certain number of agents are used for global search to find several feasible solutions with high fitness. Secondly, in order to avoid the algorithm falling into local optimum, ASA is used to carry out local optimization for each agent. Finally. The validity of the algorithm is verified by the calculation results of typical examples in the benchmark library.
【作者单位】： 北京航空航天大学机械工程及自动化学院;
【基金】：国家重大科技专项(2015ZX04005005)~~
【分类号】：TP18;TB497
【正文快照】： 网络出版地址:www.cnki.net/kcms/detail/11.2625.V.20160307.1508.001.html引用格式:李小涛,彭，

本文编号：1451477